Title: | Linear models based on business data from the pharmaceutical industry |
Authors: | Říha, David Stros, Michael |
Citation: | Trendy v podnikání = Business trends : vědecký časopis Fakulty ekonomické ZČU v Plzni. 2018, č. 1, roč. 8, s. 45-55. |
Issue Date: | 2018 |
Publisher: | Západočeská univerzita v Plzni |
Document type: | článek article |
URI: | http://hdl.handle.net/11025/31019 https://drive.google.com/drive/folders/1LxJN4JSfOhOxX_FK0xL7D4baGf4iQOAn |
ISSN: | 1805-0603 |
Keywords: | analýza podnikových dat;heterogenní datový set;hierarchický lineární model;vícenásobná regrese |
Keywords in different language: | business data analysis;heterogeneous data set;hierarchical linear model;multiple regression |
Abstract in different language: | This article describes the analysis of heterogeneous market data. For this purpose, the most relevant methodological aspects are discussed and analyses using a hierarchical linear model and multiple regression are presented. In the first step, the applied data set is presented, and the assumed hierarchical two-level structure is shown. The data are then prepared for the analysis. The data are checked for outliers, a multicollinearity check is conducted, a new variable introduced, missing values are replaced by estimated values, a transformation procedure is conducted in order to obtain normality, the data are aggregated for each hierarchical level and a sample size test is performed. The results of both methods are discussed. Finally, it is concluded that whereas the application of a hierarchical linear model appears to be one option, a multiple regression analysis can be employed instead if the quality of the data, especially the sample size, is not sufficient. |
Rights: | © Západočeská univerzita v Plzni |
Appears in Collections: | Číslo 1 (2018) Číslo 1 (2018) |
Files in This Item:
File | Description | Size | Format | |
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6_Riha_Stros.pdf | Plný text | 249,29 kB | Adobe PDF | View/Open |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/31019
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